Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 349 896 972 144 942 136 773 292 540 258 831 449 362 207 262 952 312 261 546 28
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 258 540 NA 449 831 136 207 773 292 952 362 349 261 28 312 262 896 NA NA 546 942 144 972
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 4 5 3 2 3 2 5 5 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "j" "u" "q" "y" "b" "I" "L" "D" "Q" "X"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 3 5 16
which( manyNumbersWithNA > 900 )
[1] 10 21 23
which( is.na( manyNumbersWithNA ) )
[1] 3 18 19
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 972 942 952
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 972 942 952
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 972 942 952
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "I" "L" "D" "Q" "X"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "j" "u" "q" "y" "b"
manyNumbers %in% 300:600
[1] TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE TRUE FALSE
which( manyNumbers %in% 300:600 )
[1] 1 9 12 13 17 19
sum( manyNumbers %in% 300:600 )
[1] 6
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "large" NA "small" "large" "small" "small" "large" "small" "large" "small" "small" "small" "small" "small" "small"
[17] "large" NA NA "large" "large" "small" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "large" "UNKNOWN" "small" "large" "small" "small" "large" "small" "large" "small" "small" "small"
[14] "small" "small" "small" "large" "UNKNOWN" "UNKNOWN" "large" "large" "small" "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 540 NA 0 831 0 0 773 0 952 0 0 0 0 0 0 896 NA NA 546 942 0 972
unique( duplicatedNumbers )
[1] 2 4 5 3 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 4 5 3 1
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE
which.max( manyNumbersWithNA )
[1] 23
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 972
which.min( manyNumbersWithNA )
[1] 14
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 28
range( manyNumbersWithNA, na.rm = TRUE )
[1] 28 972
manyNumbersWithNA
[1] 258 540 NA 449 831 136 207 773 292 952 362 349 261 28 312 262 896 NA NA 546 942 144 972
sort( manyNumbersWithNA )
[1] 28 136 144 207 258 261 262 292 312 349 362 449 540 546 773 831 896 942 952 972
sort( manyNumbersWithNA, na.last = TRUE )
[1] 28 136 144 207 258 261 262 292 312 349 362 449 540 546 773 831 896 942 952 972 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 972 952 942 896 831 773 546 540 449 362 349 312 292 262 261 258 207 144 136 28 NA NA NA
manyNumbersWithNA[1:5]
[1] 258 540 NA 449 831
order( manyNumbersWithNA[1:5] )
[1] 1 4 2 5 3
rank( manyNumbersWithNA[1:5] )
[1] 1 3 5 2 4
sort( mixedLetters )
[1] "b" "D" "I" "j" "L" "q" "Q" "u" "X" "y"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 1.5 6.5 1.5 3.5 9.5 9.5 3.5 6.5 6.5 6.5
rank( manyDuplicates, ties.method = "min" )
[1] 1 5 1 3 9 9 3 5 5 5
rank( manyDuplicates, ties.method = "random" )
[1] 1 8 2 3 10 9 4 5 6 7
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 1.36859221 -0.38183541 -0.30943528 -0.03977668 0.86543151
[11] 1.25225319 1.12200614 1.55306833 0.90868448 -1.46379116
round( v, 0 )
[1] -1 0 0 0 1 1 0 0 0 1 1 1 2 1 -1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 1.4 -0.4 -0.3 0.0 0.9 1.3 1.1 1.6 0.9 -1.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 1.37 -0.38 -0.31 -0.04 0.87 1.25 1.12 1.55 0.91 -1.46
floor( v )
[1] -1 -1 0 0 1 1 -1 -1 -1 0 1 1 1 0 -2
ceiling( v )
[1] -1 0 0 1 1 2 0 0 0 1 2 2 2 1 -1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
Copyright © 2021 Biomedical Data Sciences (BDS) | LUMC